Giving data the context it deserves.
A useful description starts with more than a column name.
When a data question arrives at the final table, tracing it back to the source and understanding the transformations takes time. Analysts and AI tools need context that a field name alone cannot provide.
I originated and led an applied AI initiative that uses data context to help generate table and column descriptions, with human review and feedback. It evolved from early prototypes into a production solution used across teams.
Connect lineage with meaningful metadata, evaluate draft descriptions, and keep people responsible for approval before publication.
Descriptions are intentionally high-level and omit internal data and unapproved metrics.